The Electrocochleogram (ECochG) is an electrophysiologic signal acquired from the cochlea in response to sound or electrical stimulaton. This recorded signal is a mixture of potentials generated by hair cells and nerve activity. Although many companies make products which can acquire the ECochG signal, the interpretation of that signal is largely qualitative. Our investigators have developed an algorithm that splits the recorded signal into clinically relevant metrics which can be interpreted by clinicians and audiologists. The algorithm takes the raw recorded waveform and calculates the cochlear microphonic (CM), compound action potential (CAP), summating potential (SP), and other factors. The software also makes use of biophysical modeling and machine learning to distinguish the relative contributions of inner and outer hair cells and the auditory nerve in the recorded signal.